An image capturing device is capable of capturing an image. A typical image capturing device is a camera, comprising a lens and an image sensor behind the lens. An image of an object in front of the lens is projected by the lens on the image sensor. The so produced image has a limited depth of field, and provides information on the objects in the image from one viewpoint only. The spatial resolution that can be provided in the image is restricted by the aperture of the lens.
It is known that at least some of these problems can be reduced by providing a system comprising an array of image capturing devices.
An example of such a system is a so-called plenoptic camera. A plenoptic camera, also called a light-field camera, is a camera that uses a micro lens array (also known as a lenticular lens array) to capture light field information about a scene. A microlens array is situated between the lens and the image sensor. The micro lens array refocuses light captured by the lens onto the image sensor thereby creating many small images taken from slightly different viewpoints, which images are manipulated by software to extract depth information. Each of the small images has a relatively low spatial resolution. Each part of the sensor behind the micro lens array that captures the small image through one of the microlenses of the microlens array forms in itself an image capturing device. Thus, a plenoptic camera is or acts as a system comprising an array of image capturing devices.
It is possible, on basis of the data captured by a plenoptic camera to digitally refocus on a particular plane. This is for instance explained in Stanford Tech Report CTSR 2005-02, page 1-11, “Light Field Photography with a Hand-held Plenoptic Camera”, by N G et al. However, although refocusing on a single plane is possible, the so-resulting image has a very limited depth of field. It is difficult to produce extended depth of field images. On page 6, right hand column, final paragraph of the Stanford Tech Report CTSR 2005-02 Ng et al have experimented by refocusing a light field at multiple depths and then applying a digital photomontage technique to produce a virtual output image. In the digital photomontage technique two techniques are applied: graph-cut optimization, to choose good seams within the constituent images so that they can be combined as seamlessly as possible; and gradient-domain fusion, a process based on Poisson equations, to further reduce any remaining visible artefacts in the composite. Basically the photomontage technique is a cut- and past technique, in-focus pixels of various images at various depths are combined to produce a virtual output image. Often the quality of the resulting virtual output image is dependent on using an estimated depth map so as to know which pixels are in-focus. Ng et al also produced extended depth of field by extracting a single sub-aperture image, but this technique results in quite noisy images.
The resulting images are, however, quite noisy and/or require an active role of the user.
A method and system of the opening paragraphs is discloses in “View Interpolation by Inverse Filtering: Generating the Center View using Multiview images of Circular Camera Array” by Akira Kubota, Kazuya Kodama and Yohisnori Hatori in Visual Communications and Image Processing, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6508.
In this article a method is described in which a virtual output image is reconstructed at the center of a camera array arranged on a circle. Summing up all corresponding pixel values of input images obtained from the cameras in the array with respect to multiple depth layers a candidate image is created and the virtual output image is reconstructed by inverse filtering of the candidate image. The advantage of this method is that no depth information has to be known in advance.
The known system, however, has only limited possibilities and does not provide for real-life simulating imaging in particular in interactive systems.